Cognitive analytics is the process of analyzing available information or knowledge to create, infer, deduce, or derive new information. A natural language is a written or a spoken language having a form that is employed by humans for primarily communicating with other humans or with systems having a natural language interface.
Natural language processing (NLP) is a technique that facilitates exchange of information between humans and data processing systems. For example, one branch of NLP pertains to transforming human readable or human understandable content into machine usable data. For example, NLP engines are presently usable to accept input content such as a text content or human speech, and produce structured data, such as an outline of the input content, most significant and least significant parts, a subject, a reference, dependencies within the content, and the like, from the given content.
Another branch of NLP pertains to answering questions about a subject matter based on information available about the subject-matter domain. This branch of cognitive analytics using NLP is implemented as a Question and Answer system (Q and A system).
Hereinafter, a “message” is any form of electronic communication from a sending user (sender) to one or more receiving users (recipient, recipients), unless expressly disambiguated where used. For example, a message may take the form of an email or a social media post or comment. As another example, a message may not take the form of a publication, such as a blog post or other types of communication where the message is not targeted at any particular recipient but to an unspecified audience at large.
Generally, a sender composes a message by selecting a set of recipients and putting together the content the sender intends to share with the set of recipients. In many cases, while the sender is knowledgeable about the content of the message, a recipient might not be knowledgeable or skilled enough to sufficiently comprehend the content of the message.
For example, an email message may include technical or subject-matter domain-specific content. A recipient of that content may not be technically skilled, may not have a level of expertise in the skill, may not be familiar with the subject-matter, or some combination thereof. Accordingly, the content, or the manner in which the content is presented in the message may not be suitable for the recipient's skill, skill level, or domain knowledge. Presently, the sender has no way of knowing whether all the selected recipients of the message have the needed skill set to be able to sufficiently read, understand, and/or interpret the content of the message.